Zobrazeno 1 - 10
of 61
pro vyhledávání: '"MADHAVAN, ADVAIT"'
Autor:
Yousuf, Osama, Hoskins, Brian, Ramu, Karthick, Fream, Mitchell, Borders, William A., Madhavan, Advait, Daniels, Matthew W., Dienstfrey, Andrew, McClelland, Jabez J., Lueker-Boden, Martin, Adam, Gina C.
Artificial neural networks have advanced due to scaling dimensions, but conventional computing faces inefficiency due to the von Neumann bottleneck. In-memory computation architectures, like memristors, offer promise but face challenges due to hardwa
Externí odkaz:
http://arxiv.org/abs/2404.15621
Autor:
Pocher, Liam A., Adeyeye, Temitayo N., Gibeault, Sidra, Talatchian, Philippe, Ebels, Ursula, Lathrop, Daniel P., McClelland, Jabez J., Stiles, Mark D., Madhavan, Advait, Daniels, Matthew W.
Superparamagnetic tunnel junctions are important devices for a range of emerging technologies, but most existing compact models capture only their mean switching rates. Capturing qualitatively accurate analog dynamics of these devices will be importa
Externí odkaz:
http://arxiv.org/abs/2403.11988
Autor:
Soumah, Lucile, Desplat, Louise, Phan, Nhat-Tan, Valli, Ahmed Sidi El, Madhavan, Advait, Disdier, Florian, Auffret, Stéphane, Sousa, Ricardo, Ebels, Ursula, Talatchian, Philippe
We demonstrate the miniaturization of perpendicularly magnetized superparamagnetic tunnel junctions (SMTJs) down to 50 nm in diameter. We experimentally show stochastic reversals in those junctions, with tunable mean dwell times down to a few nanosec
Externí odkaz:
http://arxiv.org/abs/2402.03452
Autor:
Gibeault, Sidra, Adeyeye, Temitayo N., Pocher, Liam A., Lathrop, Daniel P., Daniels, Matthew W., Stiles, Mark D., McClelland, Jabez J., Borders, William A., Ryan, Jason T., Talatchian, Philippe, Ebels, Ursula, Madhavan, Advait
Superparamagnetic tunnel junctions (SMTJs) are promising sources of randomness for compact and energy efficient implementations of probabilistic computing techniques. Augmenting an SMTJ with electronic circuits, to convert the random telegraph fluctu
Externí odkaz:
http://arxiv.org/abs/2312.13171
Autor:
Borders, William A., Madhavan, Advait, Daniels, Matthew W., Georgiou, Vasileia, Lueker-Boden, Martin, Santos, Tiffany S., Braganca, Patrick M., Stiles, Mark D., McClelland, Jabez J., Hoskins, Brian D.
Publikováno v:
Phys. Rev. Applied 22, 014057 (2024)
The increasing scale of neural networks needed to support more complex applications has led to an increasing requirement for area- and energy-efficient hardware. One route to meeting the budget for these applications is to circumvent the von Neumann
Externí odkaz:
http://arxiv.org/abs/2312.06446
Autor:
Phan, Nhat-Tan, Prasad, Nitin, Hakam, Abderrazak, Valli, Ahmed Sidi El, Anghel, Lorena, Benetti, Luana, Madhavan, Advait, Jenkins, Alex S., Ferreira, Ricardo, Stiles, Mark D., Ebels, Ursula, Talatchian, Philippe
Unbiased sources of true randomness are critical for the successful deployment of stochastic unconventional computing schemes and encryption applications in hardware. Leveraging nanoscale thermal magnetization fluctuations provides an efficient and a
Externí odkaz:
http://arxiv.org/abs/2311.11982
Autor:
Goodwill, Jonathan M., Prasad, Nitin, Hoskins, Brian D., Daniels, Matthew W., Madhavan, Advait, Wan, Lei, Santos, Tiffany S., Tran, Michael, Katine, Jordan A., Braganca, Patrick M., Stiles, Mark D., McClelland, Jabez J.
Publikováno v:
Physical Review Applied, 18(1) 014039 (2022)
The increasing scale of neural networks and their growing application space have produced demand for more energy- and memory-efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include
Externí odkaz:
http://arxiv.org/abs/2112.09159
Simulations of complex-valued Hopfield networks based on spin-torque oscillators can recover phase-encoded images. Sequences of memristor-augmented inverters provide tunable delay elements that implement complex weights by phase shifting the oscillat
Externí odkaz:
http://arxiv.org/abs/2112.03358
Autor:
Talatchian, Philippe, Daniels, Matthew W., Madhavan, Advait, Pufall, Matthew R., Jué, Emilie, Rippard, William H., McClelland, Jabez J., Stiles, Mark D.
Publikováno v:
Phys. Rev. B 104, 054427 (2021)
Superparamagnetic tunnel junctions (SMTJs) are promising sources for the randomness required by some compact and energy-efficient computing schemes. Coupling SMTJs gives rise to collective behavior that could be useful for cognitive computing. We use
Externí odkaz:
http://arxiv.org/abs/2106.03604
Race logic, an arrival-time-coded logic family, has demonstrated energy and performance improvements for applications ranging from dynamic programming to machine learning. However, the ad hoc mappings of algorithms into hardware result in custom arch
Externí odkaz:
http://arxiv.org/abs/2009.14243